37 results about "Torque optimization" patented technology

The invention provides an electric vehicle torque optimization method based on data driven predictive control, belongs to the technical field of electric vehicles, and aims to effectively perform optimized distribution of driving and braking torque of an electric vehicle so as to realize a tracking control method for the longitudinal velocity of the vehicle. The method comprises the steps as follows: firstly, appropriate excitation data are designed according to dynamic characteristics of a system, so that sufficient excitation for the system is guaranteed; secondly, a predictive output equation of the system is constructed by input / output data obtained by excitation; then actuator rigid constraints of a motor, a battery pack and a brake are considered, and a cost function for torque optimization control is constructed with a model predictive control algorithm; finally, an optimization problem corresponding to the cost function is solved to obtain control input which then acts on the system, so that the system is controlled. For the control algorithm, all that is required is off-line simulation experiments when the excitation data are acquired, so that the development cost is lower.

Disclosed is a tooth-slot torque optimization design-method of permanent magnetism brushless direct-current dynamo. The permanent-magnetism brushless direct-current dynamo utilizes fractional slot winding, and is characterized by the specific steps as follows: 1) construct parameterized models with finite element software to realize appropriately choosing geometric parameters of the dynamo; 2) apply optimization algorithm to optimize the design of the dynamo; 3) assemble a synthetical platform for constructing parameterized model of the dynamo and processing batch computing. Construct parameterized model with the finite element software, analyze the electromagnetic field of the dynamo, then select appropriate geometric parameter of the dynamo as optimization variable according to optimization objective and constraint condition. Programming language is applied to build the synthetical optimization platform of linking optimization algorithm and finite element computing. By inputting optimization parameters directly, users are able to call the finite element software backstage to construct parameterized models and process batch computing. The aforementioned design-method has the advantages of direct-visuality, having reasonable programming frame, fast computing, precise computing precise results and so on.

The invention discloses a distributed electric drive vehicle multi-performance optimization torque distribution method. A MPC controller based on an improved C / GMRES algorithm is adopted to conduct multi-performance optimization torque distribution. The multi-performance optimization torque distribution method comprises the steps that a longitudinal total driving torque and a yawing torque given by an upper controller are used as the torque distribution control input by the MPC controller, tire related information fed back from the vehicle is combined, a model is updated based on the wheel rotation dynamics and the tire slip rate state, the physical characteristics of the output torque of a hub motor are considered, the wheel load rate is taken as the stability constraint precondition, minimizing of the tire slip dissipation energy is taken as the optimization objective, the MPC optimal control problem is established, the improved C / GMRES algorithm is adopted to solve the problem of the torque optimization distribution quickly, and thus the real-time optimal control of vehicle stability and economy is achieved. According to the distributed electric drive vehicle multi-performance optimization torque distribution method, the MPC controller based on the improved C / GMRES algorithm is adopted to conduct multi-performance optimization torque distribution, the tire slip dissipation energy is minimized on the precondition of ensuring the vehicle stability, and the algorithm has high computational efficiency and is suitable for real-time application.

The invention discloses an energy efficiency hierarchical coordination optimization control method for a four-wheel drive extended-range electric vehicle, relates to a control method for an electric vehicle, and aims to solve the problem that the drive efficiency of an existing extended-range electric vehicle is not optimal under a complex running condition. The method comprises the following steps: calculating the total target torque Tt of two drive motors of the electric vehicle; judging whether numerical values of four nodes of a matrix grid Qi,j are empty or not, and if the numerical value of any node is empty, searching for a torque optimization allocation coefficient k by adopting a searching method, allocating the total torque Tt to the first drive motor and the second drive motor according to k, and controlling the drive motor to output target torque; otherwise calculating an average value k of the numerical values of the 4 nodes of the matrix grid Qij, adopting k as the corresponding torque optimization allocation coefficient, allocating the total torque Tt to the first drive motor and the second drive motor according to k, and controlling the drive motor to output the target torque. The method is applied to the field of vehicle designing and manufacturing.

The invention discloses an automobile back door electric stay bar moment optimization method, and relates to the technical field of automobile part design. The method comprises the following steps ofdetermining a vehicle type, and presetting a stay bar installation point layout; establishing a mechanical model for hovering the back door of the automobile by utilizing the automobile type parameters; iteratively calculating the axial force required by the stay bars at different angles in the opening and closing process of the automobile back door through a stay bar axial force calculation principle formula; designing parameters of the spring in the stay bar according to the calculated data, wherein the designed parameters of the spring need to meet the requirement for reducing the maximum stress attenuation of the spring; judging whether the designed spring force value meets the supporting rod force value requirement of suspension of the automobile back door or not, namely that the dooropening reference force is smaller than the supporting rod axial force and smaller than the door closing reference force; if yes, directly determining an optimization parameter; and if not, adjustingthe coordinates of the connecting point A of the stay bar and the automobile body and the connecting point B of the stay bar and the automobile door, and recalculating to obtain the axial force of the stay bar to be matched with the designed spring parameters. According to the present invention, the problem that an existing automobile back door electric supporting rod is poor in performance is solved.

The invention discloses a torque on-line calibration allocation control method for a four-wheel drive electric automobile and relates to an electric automobile control method. The method aims at solving the problem that energy efficiency of existing four-wheel drive system control methods still needs to be improved. The method comprises the steps that the operation condition of the automobile is detected in real time through a signal detection and conditioning unit, and the total torque Tt, generated in the operation process, of three driving motors of the electric automobile is calculated; when the SOC of a power battery is greater than or equal to the allowable operation lower limit of the electric automobile, whether values of four nodes of a matrix grid Q<i, j> in an output total torque optimum allocation coefficient matrix of front wheels and a rear shaft are null or not is judged; if the value of any node is null, a search method is adopted for searching for the torque optimization allocation coefficient k; otherwise, the mean value k of the values of the four nodes of the matrix grid Q<i, j> is calculated, and k is treated as the corresponding torque optimization allocation coefficient; and then, Tt is allocated to the two front wheel driving motors and the shaft driving motor according to k. The torque on-line calibration allocation control method is applicable to the field of automobile design and manufacturing.

A driving torque optimization control method of a pure electric vehicle comprises the steps of obtaining the energy consumption condition of high-voltage accessories of a whole vehicle system, and obtaining the current sum Iacc of the high-voltage accessories; obtaining the maximum output current Ibatt_max and the current battery total voltage Vbatt of the battery system under the current workingcondition, removing the high-voltage accessory current from the maximum output current of the battery, and considering the battery efficiency eta batt to obtain the current battery maximum output power Pbatt_max; obtaining the current motor rotating speed nrec and the opening degree theta thr of a driving pedal, and obtaining the current required torque Treq through calculation according to the current battery maximum output power Pbatt_max; obtaining efficiency MAP data of a driving motor, introducing the current motor rotating speed nrec and the calculated required torque Treq into the efficiency MAP data, and obtaining the current motor efficiency eta motor; considering the motor efficiency eta motor, and calculating the current required power Pmotorreq of the motor; and for the motor efficiency MAP data, solving the torque of the highest motor efficiency at different rotating speeds, and fitting the optimal efficiency point in the motor efficiency MAP graph into an optimal efficiency curve.

The invention relates to a dual-motor arrangement of a battery electric vehicle and a torque optimization method based on a convex optimization algorithm. The method comprises the following steps thatS1, according to a parameter of the vehicle, a longitudinal dynamics model is built; S2, a cyclic working condition of the vehicle is selected, according to the selected cyclic working condition, therequirement torque Tdem (k), requirement power Pdem (k) and biggest requirement torque Tdem, max and biggest requirement power Pdem and max of the vehicle are calculated; S3, under the premise that the capacity of a vehicle battery meets the power performance requirement, according to values of the Tdem, max and Pdex, and max, the motor size and battery size of the vehicle are selected; S4, the convex optimization processing is carried out on the motor and battery of the vehicle by the convex optimization algorithm; S5, the working state of each part of a vehicle transmission system is restricted; S6, a cost target function is determined. The method selects the dual-motor arrangement, the defect is made up that the work efficiency of the electric vehicle motor is low due to the single motor arrangement, the computing time of the optimization algorithm is quick, and the result is accurate.

The invention relates to a multivariable torque optimization control distribution method for an engine and a motor of a hybrid electric vehicle. The method comprises the following steps of: training a neural network by using actually measured engine torque and rotating speed and an equal fuel consumption value as a training set, and exporting the trained neural network when the training is finished and a training result meets a precision requirement; introducing the trained neural network in a torque division control algorithm, taking the whole vehicle working condition parameters as input, calculating an equal fuel consumption value of the engine in real time, and converting instantaneous power values of the engine and the motor into instantaneous fuel consumption; and taking the torque of the engine and the motor corresponding to the minimum instantaneous oil consumption as the optimal torque value at the moment, and outputting the optimal torque value to an engine controller and a motor controller. According to the method, the torque of the engine is not limited to three areas divided by the SOC any more, the oil consumption is calculated point by point while the external required torque of the whole vehicle is met, finally, the engine torque and the motor torque corresponding to the minimum oil consumption value are output, the working interval of the engine is optimized, and the fuel economy of the whole vehicle is further improved.

The invention relates to a driving wheel anti-skid and torque optimization fused electric vehicle stability control method, which is characterized in that the method comprises a reference model module, a fuzzy controller, a driving anti-slip controller, a torque optimization controller and a CarSim vehicle model, wherein the reference model module calculates a reference yaw velocity and a side slip angle according to driver input and a vehicle longitudinal speed; the CarSim vehicle model outputs the actual state quantity of the vehicle; the fuzzy controller calculates the additional yaw moment of the vehicle according to the reference yaw velocity, the reference side slip angle and the actual state quantity of the vehicle; and the torque optimization controller outputs the required torque of two rear wheel hub motors according to the required torque of the whole vehicle, the additional yawing torque, the tire lateral force, the vertical force and the rotating speed of the two rear wheels, the anti-slip controller is driven to control the slip rate of the left driving wheel and the right driving wheel so as to enable the slip rate to be kept near the optimal slip rate, and the two controllers complement each other, so that the stability control of the vehicle under the extreme road condition is realized.

The invention discloses a complementary type magnetic gear double-rotor motor. The motor successively comprises a motor inner rotor, an inner air gap, a motor outer rotor, an outer air gap and a stator from inside to outside. The motor inner rotor comprises an inner rotor core and main magnetic pole permanent magnets embedded in the inner rotor core, an end portion, facing a motor rotating shaft side, of each main magnetic pole permanent magnet is provided with an end slot, and the motor inner rotor further comprises auxiliary pole permanent magnets embedded between the end slots. The motor outer rotor comprises an outer rotor core and a magnetic isolation ring supporting the outer rotor core. The motor adopts axial two-section complementary structure, that is to say, a magnetic barrier is adopted to respectively divide the inner rotor and the outer rotor into two sections, the sections respectively deviate for an electrical angle, and counter potential waveform optimization, positioning torque optimization and output torque optimization are achieved; and an implementation method of the section deviation angle is achieved through special design for rotor parts, a motor part does not need to be increased, and new assembling process does not need.

The invention discloses a distributed predictive control method for a multi-motor cutter system of a heading machine. The method comprises a step of modeling a cutter driving system according to a mechanical association relationship, obtaining each motor system equation, accordingly establishing a partition system model of the heading machine cutter system, and providing a model for the torque optimization of a motor, a step of using the distributed predictive control method to design an independent distributed prediction controller for each partition based on the cutter system partition model, and carrying out optimization setting on the motor torque of the partition, and a step of introducing an iterative algorithm to realize the iterative interaction of the motor torque setting of eachpartition and performing multiple interactions of controllers in each sampling period to achieve a load balance of each partition motor. The method of the invention extends and expands a traditional centralized control algorithm and has advantages over traditional centralized control in terms of reliability, flexibility and fault tolerance.

The invention belongs to the technical field of electric vehicles, and provides an electric vehicle crawling starting control method and a device. The method comprises the steps that after crawling begins, S1, the required output torque is obtained based on the current torque and a preset vehicle speed-time curve; S2, the actual output torque and acceleration of the vehicle in the time period from the beginning of crawling to the current moment are obtained, and an actual resistance overcoming torque-time curve is determined; S3, according to the actual resistance overcoming torque-time curve, the required output torque for overcoming the predicted resistance is obtained; and S4, according to a preset judgment condition, it is determined that the vehicle executes the required output torque or the required output torque for overcoming the predicted resistance. By adopting the technical scheme in the embodiment of the invention, the uncertainty of unknown resistance can be reduced, and the problem that vehicle speed errors exist after the actual output torque is executed is optimized by obtaining the required output torque for overcoming the predicted resistance and judging whether the required output torque for overcoming the predicted resistance is executed.

The invention provides a torque optimal distribution control method for a distributed drive electric automobile and relates to a torque distribution control method for the distributed drive electric automobile. The problems that in the torque distribution manner of an existing distributed drive electric automobile under four-wheel drive and the like, tires are worn, and the running stability of the electric automobile is poor are solved. By the adoption of the torque optimal distribution control method, pressure sensors are adopted for detecting the vertical loads of tires, automobile speed sensors are adopted for detecting the transverse speeds of the tires, and rotation speed sensors are adopted for detecting the rotation speeds of the tires; signals are sent to a whole automobile controller; the whole automobile controller calculates related parameters and the tire wear power in the running process of the electric automobile according to the received signals; the obtained related parameters and the tire wear power are used for calculating the torque of four drive motors of the electric automobile, and when the tire wear power is minimum, an objective function for torque distribution control of the four motors is obtained; and according to restraint conditions, drive torque functions of the four motors are obtained. The method is suitable for torque distribution control for the distributed drive electric automobile.

The invention relates to an electromagnetic coupling vibration test system and a control strategy during high-speed rotation of a direct-drive hub motor, belongs to the field of magnetic field detection, and solves the problem that an air-gap magnetic field of the hub motor is not easy to detect in a complex working environment. The detection system comprises an upper computer and a whole vehicle experiment bench. Six wireless vibration sensors are embedded in a stator rack in a hub of the whole vehicle experiment bench, six stator armature current sensors are embedded in a stator coil, and six wireless position sensors are embedded in a rotor; and six vibration sensors are respectively embedded into the connecting parts of four driving wheels and a suspension. The upper computer establishes communication connection with a whole vehicle hub driving experiment bench sensor through wireless Bluetooth, and the interior of the upper computer is composed of a hub motor prediction robust controller, a graphical interface, an improved QSPO-LSTM torque optimization algorithm, vibration feature analysis, a gradient lifting decision tree and a series of software designs. And the rotating speed control problem caused by electromagnetic coupling vibration during high-speed rotation of the hub motor is solved through data processing by the upper computer.

The invention discloses a low voltage AC asynchronous motor high speed torque optimization design method. The above mentioned method comprises the following steps: 1) a rotor slot number of a low voltage AC asynchronous motor is set as Z2, and stator winding resistance R1, rotor winding reduced resistance R2, stator leakage inductance L1 sigma, excitation inductance Lm, rotor reduced slot leakage inductance L'2s, rotor reduced end part leakage inductance L'2e, rotor reduced harmonic wave leakage inductance L'2d, and rotor reduced skewed slot L'2sk can be acquired during the high-frequency operation of the low voltage AC asynchronous motor; 2) an optimization target can be set: min w(x); (3) an constraint condition can be determined: W(x)> alfa, and the alfa is a constant;4) the target function can be optimized to acquire the optimized rotor slot number Z2, and the rotor slot number Z2 can be acquired by the low voltage asynchronous motor via the step 3). The low voltage AC asynchronous motor high speed torque optimization design method is advantageous in that by increasing the proper rotor slot number, the high frequency torque characteristics of the low voltage AC asynchronous motor can be improved.

The invention relates to the field of mechanical arm control, in particular to a compensation result optimization method and device, electronic equipment and a storage medium. The compensation result optimization method comprises the following steps: acquiring planned motion data of the mechanical arm; acquiring actual motion data of the mechanical arm; inputting the planning motion data into the trained compensation model to obtain a moment prediction correction value; acquiring a correction coefficient according to the planning motion data, the actual motion data and the moment prediction correction value; calculating a torque optimization correction value according to the torque prediction correction value and the correction coefficient; and controlling the mechanical arm to move according to the torque optimization correction value. According to the method, the compensation result can be further optimized by utilizing the optimization model, and unreasonable compensation results are reduced, so that the stability of the mechanical arm during movement is improved.

The invention discloses a distributed electric drive vehicle multi-performance optimization torque distribution method. A MPC controller based on an improved C / GMRES algorithm is adopted to conduct multi-performance optimization torque distribution. The multi-performance optimization torque distribution method comprises the steps that a longitudinal total driving torque and a yawing torque given by an upper controller are used as the torque distribution control input by the MPC controller, tire related information fed back from the vehicle is combined, a model is updated based on the wheel rotation dynamics and the tire slip rate state, the physical characteristics of the output torque of a hub motor are considered, the wheel load rate is taken as the stability constraint precondition, minimizing of the tire slip dissipation energy is taken as the optimization objective, the MPC optimal control problem is established, the improved C / GMRES algorithm is adopted to solve the problem of the torque optimization distribution quickly, and thus the real-time optimal control of vehicle stability and economy is achieved. According to the distributed electric drive vehicle multi-performance optimization torque distribution method, the MPC controller based on the improved C / GMRES algorithm is adopted to conduct multi-performance optimization torque distribution, the tire slip dissipation energy is minimized on the precondition of ensuring the vehicle stability, and the algorithm has high computational efficiency and is suitable for real-time application.

The invention discloses a hybrid electric vehicle energy management system based on driving intention recognition. A driving intention recognition system judges whether a driving style belongs to a power mode or an economic mode according to a vehicle average acceleration and an acceleration mean variance; judging whether the acceleration state of the driver is general acceleration, gentle acceleration or emergency acceleration according to the accelerator pedal opening degree and the pedal opening degree change rate; judging whether the starting intention or the cruising speed is a low speed, a medium speed or a high speed by combining the vehicle speed with the vehicle acceleration; the working mode selection system determines a main power source according to driving intention judgment made by the driving intention recognition system and in combination with an SOC value; meanwhile, the torque optimization distribution system carries out power distribution; the method is combined with a control strategy proposed for the multimode coupling driving system, a corresponding energy management strategy is formulated, and the fuel consumption of the multimode coupling driving system is reduced.

The invention relates to a dual-motor arrangement of a battery electric vehicle and a torque optimization method based on a convex optimization algorithm. The method comprises the following steps thatS1, according to a parameter of the vehicle, a longitudinal dynamics model is built; S2, a cyclic working condition of the vehicle is selected, according to the selected cyclic working condition, therequirement torque Tdem (k), requirement power Pdem (k) and biggest requirement torque Tdem, max and biggest requirement power Pdem and max of the vehicle are calculated; S3, under the premise that the capacity of a vehicle battery meets the power performance requirement, according to values of the Tdem, max and Pdex, and max, the motor size and battery size of the vehicle are selected; S4, the convex optimization processing is carried out on the motor and battery of the vehicle by the convex optimization algorithm; S5, the working state of each part of a vehicle transmission system is restricted; S6, a cost target function is determined. The method selects the dual-motor arrangement, the defect is made up that the work efficiency of the electric vehicle motor is low due to the single motor arrangement, the computing time of the optimization algorithm is quick, and the result is accurate.

The invention provides a maximum regenerative braking torque optimization control method for a permanent magnet synchronous motor driving system. According to the invention, by comprehensively considering the T-omega external characteristic of a permanent magnet synchronous motor and the constraint of the capacity of a motor controller on the maximum braking torque output by the motor, through the design of the unit power factor control law of the permanent magnet synchronous motor and the solution of a change law of motor inductors Ld and Lq along with stator currents id and iq, real-time calculation of a current instruction value corresponding to the maximum braking torque is carried out based on an online calculation mode, accurate control of the maximum braking torque of a permanent magnet motor driving system in a full rotation speed range is completed, and the regenerative braking efficiency of the permanent magnet synchronous motor driving system is optimized; and the maximum torque optimization control method is completed based on a real-time calculation mode, has the advantages that the control real-time performance is good, and the control precision is not influenced by the inductance change in the operation process of the permanent magnet synchronous motor, and has obvious advantages in the aspects of control precision, usability and the like compared with the prior art.

The invention discloses a doubly salient permanent magnet motor phase current driving switch control method and system. Firstly, ideal flux linkage distribution and a current switch state are given. Afour-state control method of a switch on-off mode of a driving switch circuit is acquired. Through nonlinear model analysis and testing, a counter electromotive force is verified, and through dynamicmodel analysis, a result shows effectiveness of a proposed on-off control method of a current switch of a two-phase FMDSPM phase winding, and conduction time of a driving switch is prolonged so thata service life is prolonged, driving control is effectively executed on a two-phase FMDSPM motor. A two-phase motor can be formed in a two-phase winding continuous single-phase working mode, and a two-phase motor can also be formed through two-phase synchronous working, which depends on a requirement of an application occasion to output quality. An effective foundation support is provided for development of switch angle control, a speed regulation theory, a driving circuit, output torque optimization and the like.

The present application relates to a vehicle torque distribution method, device, controller and storage medium. The method includes: obtaining the power loss model of each electric drive unit at different speeds of the target vehicle; determining the wheel electric torque demand and magnitude sequence of the electric drive units on both sides of the vehicle body according to the total wheel electric torque demand of the target vehicle; In each speed state of the target vehicle, according to the power loss model of each electric drive unit and the preset wheel electric torque optimization algorithm, the minimum condition for the total power loss of all electric drive units on the same side is obtained; According to the minimum condition of the sum of unit power losses, the candidate wheel electric torque distribution of each electric drive unit is obtained; according to the total wheel electric torque demand of the target vehicle and the wheel electric torque demand and magnitude sequence of each electric drive unit on both sides of the vehicle body, Among the candidate wheel electric torque distribution methods, the optimal distribution method that satisfies the minimum sum of power losses of all electric drive units on the same side is determined.

A hybrid vehicle engine and motor multi-variable torque optimization control distribution method, using the measured engine torque and speed and fuel consumption values ​​as the training set to train the neural network, when the training is over and the training results meet the accuracy requirements, Export the trained neural network; refer to the trained neural network in the split torque control algorithm, take the vehicle operating condition parameters as input, calculate the equal fuel consumption value of the engine in real time and convert the instantaneous power value of the engine and motor into instantaneous Fuel consumption: The torque of the engine and motor corresponding to the minimum instantaneous fuel consumption is output to the engine and motor controller as the optimal torque value at this moment. The torque of the engine of the present invention is no longer limited to the three areas divided by the SOC. While satisfying the external demand torque of the vehicle, the fuel consumption is calculated point by point, and finally the engine and motor torque corresponding to the minimum fuel consumption are output, optimizing the The working range of the engine further improves the fuel economy of the vehicle.

A speed and torque optimizer for a drive train includes an input shaft coupled with a primary driver having a pinion gear thereon that engages an input ring gear. The input ring gear is affixed to a first end of a carrier shaft having an output ring gear on an opposing end. The output ring gear engages an output pinion gear mounted on an output shaft. The input ring gear is larger in diameter than the output ring gear and therefore has more teeth. Because the input and output ring gears are mounted on the same shaft, they rotate at the same speeds thereby rotating the output pinion gear at a faster speed than the input pinion gear. The intermeshing gear teeth have a predefined curvature, pitch diameter and length to further accomplish increased speed at the output shaft while minimizing torque loss.

The invention provides a four-wheel torque distribution in-loop test device under an extreme working condition and a torque optimization method, the four-wheel torque distribution in-loop test device comprises an upper computer, a hub motor driving automobile and a torque distribution controller, the upper computer communicates with a vehicle controller through a CAN bus, and the vehicle controller performs torque distribution and sends a torque control instruction to a motor controller. The upper computer comprises a simulation test working condition library, control testing under the extreme working condition of severe differential vibration of wheels can be achieved, vehicle state parameters are obtained through sensor multi-signal fusion, a multi-target optimization problem of a real-time adjustment target function is established based on the minimum motor energy consumption, the optimal slip rate and the real-time vehicle state parameters. An improved NAGA-II optimization algorithm is adopted for torque distribution, and control optimization under the extreme working condition is achieved through torque compensation.

The invention relates to a torque optimization distribution control method for a four-wheel drive electric vehicle, which formulates a motor efficiency calculation model for the motor under driving conditions, coasting conditions and starting conditions, and divides the vehicle driving mode into two-axis driving modes , single-axis driving mode, dual-axis starting mode and single-axis starting mode, respectively determine the power consumption calculation methods in different modes, and obtain the torque distribution coefficient with the goal of energy optimization through the offline global optimization algorithm. In order to avoid excessive torque changes in the control process, a torque optimization distribution model oriented to the torque change rate is established, and the dynamic weight factors are determined by fuzzy control rules, and finally the results of the four-wheel torque distribution are determined; this method reduces energy consumption and The current fluctuation in the motor is the target, and the torque distribution coefficient for energy saving and torque change rate and the corresponding global optimal efficiency are calculated, which greatly improves the cruising range of electric vehicles and ensures the safety and long-term use of in-wheel motors .

The invention relates to a model predictive control method of a permanent magnet synchronous motor based on a dead zone effect, which belongs to the technical field of control. The purpose of the present invention is to take the inverter switch as the core, improve the dead time of the actual inverter, realize the accurate and fast dynamic response of the torque, and improve the efficiency of the working area of ​​the motor. Model predictive control method for magnetic synchronous motor. The steps of the invention are: permanent magnet synchronous motor and inverter dead zone modeling, finite set MPC torque optimization control considering the dead zone. The model predictive control method adopted in the present invention can effectively reduce the internal power consumption of the motor drive system (including motor copper loss and inverter switching loss) and conduction loss), thereby improving the efficiency of the motor working area and improving economy.